ERC FUNDED PROJECTS

Serotonin (5-HT) is a central neuromodulator and a major target of therapeutic psychoactive drugs, but relatively little is known about how it modulates information processing in neural circuits. The theory of predictive coding postulates that the brain combines raw bottom-up sensory information with top-down information from internal models to make perceptual inferences about the world. We hypothesize, based on preliminary data and prior literature, that a role of 5-HT in this process is to report prediction errors and promote the suppression and weakening of erroneous internal models. We propose that it does this by inhibiting top-down relative to bottom-up cortical information flow. To test this hypothesis, we propose a set of experiments in mice performing olfactory perceptual tasks. Our specific aims are: (1) We will test whether 5-HT neurons encode sensory prediction errors. (2) We will test their causal role in using predictive cues to guide perceptual decisions. (3) We will characterize how 5-HT influences the encoding of sensory information by neuronal populations in the olfactory cortex and identify the underlying circuitry. (4) Finally, we will map the effects of 5-HT across the whole brain and use this information to target further causal manipulations to specific 5-HT projections. We accomplish these aims using state-of-the-art optogenetic, electrophysiological and imaging techniques (including 9.4T small-animal functional magnetic resonance imaging) as well as psychophysical tasks amenable to quantitative analysis and computational theory. Together, these experiments will tackle multiple facets of an important general computational question, bringing to bear an array of cutting-edge technologies to address with unprecedented mechanistic detail how 5-HT impacts neural coding and perceptual decision-making.

2 486 074 €

Start date: 2016-01-01, End date: 2020-12-31

The brain evolves, develops, and operates in the context of animal movements. As a consequence, fundamental brain functions such as spatial perception and motor control critically depend on the precise knowledge of the ongoing body motion. An accurate internal estimate of self-movement is thought to emerge from sensorimotor integration; nonetheless, which circuits perform this internal estimation, and exactly how motor-sensory coordination is implemented within these circuits are basic questions that remain to be poorly understood. There is growing evidence suggesting that, during locomotion, motor-related and visual signals interact at early stages of visual processing. In mammals, however, it is not clear what the function of this interaction is. Recently, we have shown that a population of Drosophila optic-flow processing neurons —neurons that are sensitive to self-generated visual flow, receives convergent visual and walking-related signals to form a faithful representation of the fly’s walking movements. Leveraging from these results, and combining quantitative analysis of behavior with physiology, optogenetics, and modelling, we propose to investigate circuit mechanisms of self-movement estimation during walking. We will:1) use cell specific manipulations to identify what cells are necessary to generate the motor-related activity in the population of visual neurons, 2) record from the identified neurons and correlate their activity with specific locomotor parameters, and 3) perturb the activity of different cell-types within the identified circuits to test their role in the dynamics of the visual neurons, and on the fly’s walking behavior. These experiments will establish unprecedented causal relationships among neural activity, the formation of an internal representation, and locomotor control. The identified sensorimotor principles will establish a framework that can be tested in other scenarios or animal systems with implications both in health and disease.

1 500 000 €

Start date: 2017-11-01, End date: 2022-10-31

A great deal is known about the neural basis of associative fear learning. However, many animal species are able to use social cues to recognize threats, a defence mechanism that may be less costly than learning from self-experience. We have previously shown that rats perceive the cessation of movement-evoked sound as a signal of danger and its resumption as a signal of safety. To study transmission of fear between rats we assessed the behavior of an observer while witnessing a demonstrator rat display fear responses. With this paradigm we will take advantage of the accumulated knowledge on learned fear to investigate the neural mechanisms by which the social environment regulates defense behaviors. We will unravel the neural circuits involved in detecting the transition from movement-evoked sound to silence. Moreover, since observer rats previously exposed to shock display observational freezing, but naive observer rats do not, we will determine the mechanism by which prior experience contribute to observational freezing. To this end, we will focus on the amygdala, crucial for fear learning and expression, and its auditory inputs, combining immunohistochemistry, pharmacology and optogenetics. Finally, as the detection of and responses to threat are often inherently social, we will study these behaviors in the context of large groups of individuals. To circumvent the serious limitations in using large populations of rats, we will resort to a different model system. The fruit fly is the ideal model system, as it is both amenable to the search for the neural mechanism of behavior, while at the same time allowing the study of the behavior of large groups of individuals. We will develop behavioral tasks, where conditioned demonstrator flies signal danger to other naïve ones. These experiments unravel how the brain uses defense behaviors as signals of danger and how it contributes to defense mechanisms at the population level.

1 412 376 €

Start date: 2013-12-01, End date: 2018-11-30

You’re faced with a difficult choice. What do you do? Most people will, either explicitly or implicitly, weigh the possible consequences their decision. This involves an internal journey through possible events. Its these kinds of dynamic processes and their mapping onto behavior that characterize higher brain function. And yet, their very internal nature is both what makes them of critical interest and so difficult to study. Here, we propose to study a simple, well-controlled decision-making behavior wherein mice have to generate a dynamic, internal representation of elapsed time in order to make choices that result in reward. We focus on frontal cortico-basal ganglia circuits and their dopaminergic inputs that together are broadly implicated in cognition and involved in the production of this particular behavior. We have demonstrated previously that striatal population dynamics and dopamine neuron activity both correlate with and exert control over animals’ judgments. Having identified key signals at multiple stages of the BG circuit related to this decision in rats and mice, my laboratory is now uniquely poised to dissect the circuit mechanisms by which such signals are generated and transformed into actions. Specifically, we will 1) Measure activity of specific cell types at multiple stages of the BG as mice judge duration. 2) Image and manipulate the activity of DA neurons while recording from neural populations in the BG to determine the relationship between neuromodulatory input, neural dynamics, and behavior. 3) Relate the activity of cortico-striatal inputs to striatal responses during behavior to understand the computational and circuit bases of striatal activity. These experiments promise to unlock deep mysteries regarding how animals free themselves from the immediacy of the current moment, learning, planning, and choosing their path toward a safer, more fruitful, and satisfying existence.

2 000 000 €

Start date: 2018-04-01, End date: 2023-03-31